Blockage of the Monoamine Oxidase by a Natural Compound to Overcome Parkinson’s Disease via Computational Biology

Sherafatizangeneh, Mahsa; Farshadfar, Chiako; Mojahed, Nooshin; Noorbakhsh, Akbar; Ardalan, Noeman

doi:10.1142/s2737416522500156

Cited by 8 publications

(5 citation statements)

References 68 publications

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“…Understanding the molecular mechanisms of diseases is crucial for developing effective diagnostic tools and therapeutic interventions, as has been demonstrated in numerous studies [40][41][42][43][44][45][46]. Genetic disorders are frequently caused by missense mutations in specific proteins, leading to malfunctioning proteins and subsequent disease phenotypes.…”

Section: Discussionmentioning

confidence: 99%

Most Monogenic Disorders Are Caused by Mutations Altering Protein Folding Free Energy

Pandey,

Alexov

2024

IJMS

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Revealing the molecular effect that pathogenic missense mutations have on the corresponding protein is crucial for developing therapeutic solutions. This is especially important for monogenic diseases since, for most of them, there is no treatment available, while typically, the treatment should be provided in the early development stages. This requires fast targeted drug development at a low cost. Here, we report an updated database of monogenic disorders (MOGEDO), which includes 768 proteins and the corresponding 2559 pathogenic and 1763 benign mutations, along with the functional classification of the corresponding proteins. Using the database and various computational tools that predict folding free energy change (ΔΔG), we demonstrate that, on average, 70% of pathogenic cases result in decreased protein stability. Such a large fraction indicates that one should aim at in silico screening for small molecules stabilizing the structure of the mutant protein. We emphasize that knowledge of ΔΔG is essential because one wants to develop stabilizers that compensate for ΔΔG, but do not make protein over-stable, since over-stable protein may be dysfunctional. We demonstrate that, by using ΔΔG and predicted solvent exposure of the mutation site, one can develop a predictive method that distinguishes pathogenic from benign mutations with a success rate even better than some of the leading pathogenicity predictors. Furthermore, hydrophobic–hydrophobic mutations have stronger correlations between folding free energy change and pathogenicity compared with others. Also, mutations involving Cys, Gly, Arg, Trp, and Tyr amino acids being replaced by any other amino acid are more likely to be pathogenic. To facilitate further detection of pathogenic mutations, the wild type of amino acids in the 768 proteins mentioned above was mutated to other 19 residues (14,847,817 mutations), the ΔΔG was calculated with SAAFEC-SEQ, and 5,506,051 mutations were predicted to be pathogenic.

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Section: Discussionmentioning

confidence: 99%

Most Monogenic Disorders Are Caused by Mutations Altering Protein Folding Free Energy

Pandey,

Alexov

2024

IJMS

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“…The use of location-specific superior variety seeds is an alternative in efforts to increase soybean production. In order to increase the availability of superior seeds, various efforts have been made in the seed sector, including by releasing new superior varieties, both locally and nationally, as a result of plant breeding (Habtegebriel and Abebe, 2023;Sherafatizangeneh et al, 2022;Ali et al, 2022). There are more than 70 soybean varieties that have been released and disseminated to farmers, but it is necessary to study the level of adaptation and stability in various agro-ecosystems such as irrigated paddy fields, rain-fed paddy fields and land so that varieties with high yields are known in these agro-systems (Amrate et al, 2023;Farhud and Mojahed, 2022).…”

Section: Methodsmentioning

confidence: 99%

Molecular analysis of Karawang local soybean genotypes with national superior varieties based on SSR analysis

Komariah,

Wahyuni,

Ramdhani

et al. 2023

Braz. J. Biol.

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The aim of this study was to analyze the similarities between the Karawang local superior varieties and several national superior varieties based on chromosome analysis or allele size. Analysis were carried out in the laboratory of the Biogen Research Institute in 2021. There were 9 genotypes analyzed, consisting of 8 national superior varieties, namely NS Karawang, Argomulyo, Grobogan, Anjasmoro, Devon-1, Detap-1, Dena-1 and Dena-2 and 1 Karawang local soybean genotypes. The results of the analysis show that Karawang local soybean has a difference with the national superior variety. The similarity of local soybeans from Karawang to NS Karawang with varieties Agromulyo and Grobogan is 68%, with soybean varieties Anjasmoro and Devon-1 is 71%, while with soybeans Detap-1, Dena-1 and Dena-2 is 76%.

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“…On the basis of ordered logit model after SMOTE it seems reasonable to clarify the boundaries of classes and thereby improve the quality of classification. For this case Tomek Links method was used, however its implementation to a sample had little improvement on results of modelling (see Table 4) (Sherafatizangeneh et al, 2022). This indicates, that the to improve the accuracy of prediction on this model the other types of machine learning models should be implemented.…”

Section: Ordered Discrete Choice Model For Evaluating the Efficiency ...mentioning

confidence: 99%

Evaluating Machine Learning Models for Healthcare Services Efficiency

Sukiasyan

2023

Br. J. Ed., Tech. Soc.

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Resumo. O artigo é dedicado ao problema de avaliação da qualidade dos cuidados de saúde utilizando algoritmos de aprendizagem de máquina. Propõe-se avaliar o termo categórico "qualidade dos cuidados de saúde" como variável discreta com base em dados sobre o resultado do tratamento, fornecidos por um dos principais hospitais da Rússia. É fornecida uma análise preliminar das variáveis dependentes e explicativas. São analisadas as estatísticas dos resultados do tratamento em função da idade e sexo dos pacientes. A necessidade de redução do conjunto de dados inicial é justificada. São propostas as formas de correção do desequilíbrio no conjunto de dados, como SMOTE e Tomek Links. Com base nos dados corrigidos, foram projetados modelos logit ordenados e Random Forest. É apresentada a análise comparativa de vários modelos. As desvantagens de cada modelo são explicadas. O modelo logit ordenado em dados balanceados permitiu determinar os fatores que têm maior impacto positivo no resultado do tratamento, bem como o modelo Random Forest tornou as previsões tão precisas quanto possível. Com base nos resultados obtidos, são feitas recomendações para melhorar a eficiência dos cuidados de saúde no âmbito de um determinado hospital.

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Blockage of the Monoamine Oxidase by a Natural Compound to Overcome Parkinson’s Disease via Computational Biology

Cited by 8 publications

References 68 publications

Most Monogenic Disorders Are Caused by Mutations Altering Protein Folding Free Energy

Most Monogenic Disorders Are Caused by Mutations Altering Protein Folding Free Energy

Molecular analysis of Karawang local soybean genotypes with national superior varieties based on SSR analysis

Evaluating Machine Learning Models for Healthcare Services Efficiency

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